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Dynamic General Equilibrium Models I

Description

A time discrete and stochastic version of the Ramsey model (which is presented in the course "Advanced Macroeconomics") forms the basis of a broad strand of empirical macroeconomic research concerning the determinants of economic growth and business cycles. Most of this work is too complex to allow for an analytical solution of the underlying model. This course shows how to tackle this problem by introducing several computer algorithms which provide a numerical approximation of the models solution.

Course Outline

  1. The Ramsey Model
    1. Description
    2. Lagrangian Approach and Dynamic Programming
    3. Saddle Path
    4. Solution Strategies
      1. Linear Approximation of the Policy Function
      2. Linearizing the System of Difference Equations
    5. Diggin' Deeper: Quadratic Approximation of the Policy Function
  2. The Stochastic Growth Model
    1. Markov Processes
    2. The Model
    3. Lagrangian Approach and Dynamic Programming
    4. Log-Linear Approximation
  3. Stochastic Dynamic General Equilibrium Models
    1. Linear Quadratic Models
    2. Computation of the Policy Functions
  4. Hansen's Divisible Labor Model
    1. Labor Supply, Preference Constraints, and Assumptions regarding the Production Technology
    2. The Decentralized Economy
    3. Model Calibration
    4. Model Evaluation

Reading List

Main Texts

Heer, Burkhard and Alfred Maußner, Dynamic General Equilibrium Modelling, Springer: Berlin 2nd Edition 2009
Stokey, Nancy L., Robert E. Lucas, Jr. with Edward C. Prescott, Recursive Methods in Economic Dynamics, Harvard University Press: Cambridge, MA u.a. 1989

Complementary Reading

Burnside, Craig, Real Business Cycle Models: Linear Approximation and GMM Estimation, Mimeo 1999
McCandless, George, The ABCs of RBCs, Harvard University Press, Cambridge MA 2008
Grandmont, Jean-Michel, Nonlinear Difference Equations, Bifurcations and Chaos: An Introduction, Centre D'Etudes Prospectives D'Economie Mathematique Appliquees A La Planification (CEPREMAP) #8811, 1988
Judd, Kenneth L., Numerical Methods in Economics, MIT Press: Cambridge, MA u.a. 1998
King, Robert G., Charles I. Plosser und Sergio Rebelo, Production, Growth and Business Cycles I, The Basic Neoclassical Model, Journal of Monetary Economics, 21, 1988, 195-232
King, Robert G., Charles I. Plosser und Sergio Rebelo, Production, Growth and Business Cycles II, New Directions, Journal of Monetary Economics, 21, 1988, 309-341
Marimon, Ramon und Andrew Scott (Eds.), Computational Methods for the Study of Dynamic Economies, Oxford University Press: Oxford, New York 1999
Maußner, Alfred, Konjunkturtheorie, Springer: Berlin, 1994
Maußner, Alfred und Rainer Klump, Wachstumstheorie, Springer: Berlin, 1996
Taylor, John B. und Harald Uhlig, Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods, Journal of Business & Economic Statistics, 8, 1990, 1-17
Uhlig, Harald, A Toolkit for Analyzing Nonlinear Dynamic Stochastic Models Easily, Mimeo, University of Tilburg, o.J.

© Alfred Maußner 2012

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